Wyniki wyszukiwania - BazTech

1

A fuzzy logic-based multi-sensor diagnostic system for traction motor bearings in railway applications

Ahmadov Heybatulla, Manafov Elshan, Guliyev Huseyngulu, Huseynov Farid

Transport Problems

|

2025

|

T. 20, z. 2

73--84

EN

DOI: 10.20858/tp.2025.20.2.06 Keywords: traction motor bearings; fault diagnosis; fuzzy products; linguistic variables; expert system Heybatulla AHMADOV1, Elshan MANAFOV2*, Huseyngulu GULIYEV3, Farid HUSEYNOV4 A fuzzy logic-based multi-sensor diagnostic system for traction motor bearings in railway applications This article focuses on the diagnosis of the bearings of the traction motors of electric railway and subway trains. One of the main sources of mechanical failures in a traction motor is its bearings. The failure of traction motor bearings, the factors that cause these failures, and the diagnostic methods for detecting them are investigated. At this time, faults in traction motor bearing monitoring systems are determined only by temperature. In this work, it is proposed to use a system with temperature, vibration, and noise to determine the technical condition of bearings. Such a multi-parameter system, unlike traditional ones, will help determine specific defects at an early stage. The expert system’s model, based on fuzzy logic and diagnostic parameters, can accurately predict the likelihood of bearing faults in real-time under changing operating conditions. A fuzzy expert system represents knowledge in the form of fuzzy productions and linguistic variables. The expert system model was developed using the Mamdani fuzzy inference algorithm of the Fuzzy Logic Toolbox package in the MATLAB computing environment. The application of fuzzy logic in generating a knowledge base and inference processes enables the formalization of a process for evaluating technical conditions based on incomplete, faulty, and potentially erroneous information and for making decisions about fault identification.

2

Aplikacja wspomagająca tworzenie postaci do systemu "Dungeons and Dragons"

Lewandowski Karol, Pakuła Michał

Studia i Materiały Informatyki Stosowanej

|

2025

|

T. 17, nr 1

59--65

PL

Artykuł poświęcony jest opracowaniu aplikacji (systemu eksperckiego) wspierającej początkujących graczy w procesie tworzenia postaci do piątej edycji systemu „Dungeons and Dragons” (D&D 5e). W pracy przedstawiono zwięzły opis systemu DnD i historie jego powstania, aplikacji, drzewo decyzyjne systemu eksperckiego. Ponadto uwzględniono informacje dotyczące wykorzystanych narzędzi oraz zastosowanych rozwiązań technologicznych.

EN

The paper is devoted to the development of an application (expert system) to supportnoviceplayers in the character creation process for the fifth edition of the ‘Dungeons and Dragons’ system (D&D 5e). The paper presents a brief description of the DnD system and the history of its creation, the application, the decisiontree of the expert system. In addition, information on the toolsused and the technological solutions employed are included.

3

AI-based expert system design for optimisation of heavy metal adsorption on waste-derived adsorbents

Gheibi Mohammad, Hajiahmadi Zahra, Jaromin-Gleń Katarzyna, Eftekhari Mohammad, Behzadian Kourosh, Černík Miroslav, Wacławek Stanisław

Chemistry-Didactics-Ecology-Metrology

|

2025

|

R. 30, NR 1-2

47--65

EN

Heavy metal contamination in wastewater is a major global problem that requires effective, automated, and sustainable treatment systems capable of linking laboratory-scale adsorption processes to intelligent large-scale operation. This work introduces a novel Expert System (ES) that combines a Genetic Algorithm (GA), Artificial Neural Networks (ANN), and Monte Carlo (MC) analysis for the automated removal of heavy metals using adsorbents obtained from Low-Density Concrete waste. This research is significant because adsorption systems are complex to automate due to their nonlinear behaviour and sensitivity to fluctuating operating conditions. By facilitating intelligent process control and optimisation, the system overcomes the main drawback of adsorption technology, which is its lack of automation. Experimental datasets for Pb2+, Co2+ and Mn2+ removal were used to train the ANN, which predicts removal from inputs (pH, adsorbent mass, contact time, initial concentration). GA then used this trained ANN to optimise these same factors. According to the sensitivity analysis, the most important control variables in heavy metal adsorption were heavy metal type, pH, and adsorbent mass. The ANN model demonstrated strong predictive performance (R2 = 0.908, RMSE = 7.43 %), enabling GA to optimise process conditions and achieve removal efficiencies of 100 % (Pb2+), 87.8 % (Co2+), and 71.62 % (Mn2+) under identified optimal operating parameters. Operational reliability measured by MC simulations showed Co2+ had a higher variability (CV: Coefficient of Variation = 5.39 %) than Mn2+ (CV = 3.29 %) and Pb2+ (CV = 2.13 %), which had minimal uncertainty. Using resources from the circular economy, the ES provides a framework for a digital twin of an Industry 4.0-compliant water treatment system that enables translation of lab-based procedures into practical applications.

4

Znaczenie sztucznej inteligencji we wspomaganiu procesu beztlenowej fermentacji odpadów kuchennych zawierających bioplastiki

Arendt Ryszard, Kopczyński Andrzej, Hupka Jan, Grabowiec Aleksandra

Przemysł Chemiczny

|

2024

|

T. 103, nr 6

711--719

PL

Przebiegu procesu fermentacji anaerobowej nie można w pełni sformalizować. W tym odniesieniu pożądane jest wykorzystanie metod sztucznej inteligencji (AI) i uczenia maszynowego do monitoringu i sterowania procesami i operacjami jednostkowymi w celu uzyskania bardziej wydajnych metod prowadzenia procesu i ilości produktów końcowych. Akwizycja danych odbywa się przez automatyczny monitoring oraz poprzez badania analityczne. Wiedzę opisującą prowadzenie procesu fermentacji anaerobowej zestawiono w postaci reguł: IF (przesłanka) THEN (konkluzja). Zestawiony zbiór reguł tworzy bazę wiedzy systemu ekspertowego prowadzenia procesu wraz ze wskazówkami dla operatora. Reguły wiedzy są aktualizowane i rozwijane w trakcie prowadzenia procesu, zaś zastosowanie AI zapewnia zachowanie wiedzy operatorów przy zmianach personelu obsługi reaktorów. Przedstawiono budowę laboratoryjnego stanowiska fermentacji anaerobowej odpadów kuchennych i żywnościowych, stosowane urządzenia techniczne, strukturę systemu AI oraz wybrane reguły wiedzy.

EN

Artificial intelligence (AI) and machine learning were used to obtain more effective methods for conducting the digestion process and achieving final products. Data acquisition was carried out by an automatic monitoring and anal. research. The knowledge describing the anaerobic digestion process was summarized in the form of rules: IF (premise) THEN (conclusion). The compiled set of rules created a knowledge base of the expert system, which was used to run the anaerobic digestion process and provided instructions to the operator. Knowledge rules were updated and developed during the process. The construction of a mobile laboratory system for the anaerobic digestion of kitchen and food waste, the tech. devices, the structure of the AI system, and selected knowledge rules were presented.

5

The expert system supporting decision-making in the process of vegetable pests extermination during vegetation period

Sojak Mariusz, Głowacki Szymon, Tulej Weronika, Bryś Andrzej, Hutsol Taras, Horetska Iryna, Stroianovska Liliia, Rozkosz Anna, Prístavka Miroslav

Agricultural Engineering

|

2023

|

Vol. 27, No. 1

331--348

EN

The paper presents a computer system supporting the identification of vegetable pests during the vegetation period and the way in which it works on the example of red beet. The objective was to develop an expert system to facilitate the identification of pests and suggest an appropriate method of controlling them. Filling the database with the knowledge applying to one narrow area of knowledge turns the expert system framework into an expert system in this area of knowledge. The system consists of the expert system and the database in the form of text files, which contain additional explanations. The user of the expert system - “DSS - pest control” needs to answer the following questions: in the first stage the user selects the diagnosed vegetable, in the second stage, the user selects the symptom or symptoms on the above-ground vegetable part, in the third stage, the user selects the symptom or symptoms on the below-ground vegetable part. The designed decision support system (“DSS - pest control”) may be used by individual vegetable growers. It may also serve as an educational program, e.g. for students who want to find out more about the specific areas of knowledge as well as for scientists and researchers.

PL

Artykuł przedstawia system komputerowy wspomagający identyfikację szkodników warzyw podczas procesu wegetacji, a także sposób jego działania na przykładzie buraka czerwonego. Celem było opracowanie systemu ekspertowego ułatwiającego identyfikację szkodników oraz zaproponowanie odpowiedniej metody ich zwalczania. Wypełnienie bazy wiedzy informacjami odnoszącymi się do wąskiego obszaru wiedzy zamienia system ekspertowy w system w danej dziedzinie wiedzy. System składa się z systemu ekspertowego oraz bazy danych w postaci plików tekstowych, które zawierają dodatkowe wyjaśnienia. Użytkownik systemu ekspertowego - "DSS - zwalczanie szkodników" musi odpowiedzieć na następujące pytania: w pierwszym etapie użytkownik wybiera diagnozowane warzywo, w drugim etapie użytkownik wybiera objaw lub objawy na nadziemnej części warzywa, w trzecim etapie użytkownik wybiera objaw lub objawy na podziemnej części warzywa. Zaprojektowany system wspomagania decyzji ("DSS - zwalczanie szkodników") może być stosowany przez indywidualnych plantatorów warzyw. Może również służyć jako program edukacyjny, np. dla studentów, którzy chcą pogłębić swoją wiedzę, może być także pomocny dla naukowców i badaczy.

6

Application of sample advisory systems in medicine

Woehl Agnieszka, Zapotoczny Kacper, Żaba Julia, Nagi Łukasz

Sustainable Production, Instrumentation and Engineering Sciences

|

2022

|

vol. 1, nr 1

13--17

EN

Artificial intelligence is a field that has been rapidly developing in various areas of knowledge in recent years. Its application in medicine can support the intensive development of research in health care and improve and ac-celerate the operation of many medical facilities. This article presents sev-eral examples of expert systems that can find application in diagnosing and preparing a patient for selected tests. Expert systems can also find appli-cation in the rapid selection of rehabilitation, medical or support equip-ment and devices with which medical facilities are supplied. In this article, the reader will also find a sample application that will perform this func-tion. The article presents the elements of which a correct expert system should consist. For each application, tests have been carried out to show the correctness of the system. The purpose of the article was to show the capabilities of the expert system and its application in medical fields.

7

Optimization model to manage ship fuel consumption and navigation time

Rudzki Krzysztof, Gomulka Piotr, Hoang Anh Tuan

Polish Maritime Research

|

2022

|

nr 3

141--153

EN

Owners of vessels are interested in the lowest possible operating costs. These costs are mainly related to fuel consumption during navigation. To manage it rationally, the main decision-making problem is selecting the proper parameters of the ship’s propulsion system during navigation. In practice, operators of ships equipped with controllable pitch propellers controlled in manual mode make a selection of the commanded outputs based on their own knowledge, intuition, and all accessible information regarding sea conditions. In many cases, their decisions are unreasonable or incorrect. Therefore, it would be desirable to support their decision-making in selecting the commanded outputs. For this reason, we have decided to develop a decision support system in the form of an expert system. This computer-aided system supports the selection of the commanded outputs of the ship’s propulsion system. The most important component of this system is the two-criteria optimization model, allowing the rational management of the ship fuel consumption and navigation time.

8

Application of predictive maintenance in the packaging production

Palchevskiy Bogdan, Krestyanpol Lyubov

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

|

2022

|

T. 12, nr 3

27--33

EN

To solve the problem of predictive maintenance for packaging manufacturing, we propose a hybrid model that optimizes the maintenance plan. The model is based on monitoring the state of many components of a multi-position automatic packaging machine and makes it possible to predict their future malfunctions and estimate the remaining service life of the equipment. The effectiveness of the proposed solution is demonstrated with the help of a real industrial multi-position machine for the automatic production of film bags and packaging of paste in them. The methodology is based on the analysis of diagnostic information using an expert system.

PL

Aby rozwiązać problem predykcyjnego utrzymania ruchu w produkcji opakowań, proponujemy hybrydowy model optymalizujący plan utrzymania ruchu. Model ten opiera się na monitorowaniu stanu wielu komponentów wielostanowiskowej automatycznej maszyny pakującej i umożliwia przewidywanie ich przyszłych awarii oraz szacowanie pozostałego czasu eksploatacji urządzenia. Skuteczność proponowanego rozwiązania została zademonstrowana na przykładzie rzeczywistej przemysłowej maszyny wielostanowiskowej do automatycznej produkcji torebek foliowych i pakowania w nie pasty. Metodyka opiera się na analizie informacji diagnostycznych z wykorzystaniem systemu eksperckiego.

9

Conceptual Design of an Anti-collision System for Light Rail Vehicles

Ważny Mariusz, Falkowski Krzysztof, Wróblewski Mirosław, Wojtowicz Konrad, Marut Adam

Problemy Mechatroniki : uzbrojenie, lotnictwo, inżynieria bezpieczeństwa

|

2021

|

Vol. 12, Nr 1 (43)

9--26

EN

This paper presents the concepts for an anti-collision system intended for trams. The purpose of the anti-collision system is to develop and provide information to support the driver’s decision to initiate the braking of a tram. The anti-collision system is based on the processing of data from multiple sources (obstacle detection, image processing, and visual light communication system) and an expert system. The information about the road situation is visually presented on HUD (Head-up Display) of the driver.

PL

W artykule przedstawiono koncepcje systemu antykolizyjnego przeznaczonego dla pojazdów szynowych. Zadaniem systemu jest wypracowanie informacji wspomagającej motorniczego w podjęciu decyzji o rozpoczęcie procesu hamowania. System opary jest na wykorzystaniu informacji z wielu źródeł (układu wykrywania przeszkód, układu rozpoznania obrazowego, układu komunikacji świetlnej) i na podstawie algorytmu zaimplementowanego w systemie eksperckim, zobrazowaniu informacji dla motorniczego na wyświetlaczu przeziernym.

10

Intelligent System in the Context of Business Process Modelling

Yaremko Svetlana A., Kuzmina Elena M., Savina Nataliia B., Gromaszek Konrad, Yeraliyeva Bakhyt, Borankulova Gauhar

International Journal of Electronics and Telecommunications

|

2021

|

Vol. 67, No. 2

163--168

EN

The article deals with the features and characteristics of intelligent systems for modelling business processes. Their classification was made and criteria for comparison were developed. According to the comparative analysis of existing expert systems for intelligent analysis, a reasonable choice of system for modelling business processes of a particular enterprise has been carried out. In general, it was found that the introduction of intelligent systems for modelling business processes of the enterprise and forecasting its activities for future allows management of the company to obtain relevant and necessary information for the adoption of effective management decisions and the development of a strategic plan.

11

Monitoring and management of geoengineering repositories of radioactive waste

Yeremeyev Igor, Dychko Alina, Kyselov Volodymyr, Zaichenko Stefan

Architecture Civil Engineering Environment

|

2021

|

Vol. 14, no. 3

103--109

EN

The paper provides the approach to the management of the repositories of radioactive waste, which include monitoring of contaminants migration into environment in case of natural or technogenic accidents which may influence on soil, subsoil waters and repository’ installations structures. The aim of the research is the development of system of estimation of radioactive state of the environment in the area of radioactive repository, based on the cumulative data, the knowledge base, set of rules of production, logical deduction gear and conclusion building gear by means of uncertain and incomplete input data. It is proposed the use of several models for the spectral characteristics of radioactive pollutants migration. The evaluation of possible damages of repository containment is made. The heuristics for the radioactive waste repository expert system are developed. The proposed procedure of quality definition of decision making for the radioactive waste repositories management should take into account the reliability of information about the state of the radioactive repository.

12

Aplikacja na platformę Android z systemem ekspertowym jako rozwiązanie problemu właściwego żywienia koni

Piszcz Adrianna, Mikołajewski Dariusz

Studia i Materiały Informatyki Stosowanej

|

2020

|

T. 12, nr 1

5--9

PL

Celem badania jest stworzenie aplikacji wspomagającej prawidłowe żywienie koni na platformę Android. Aplikacja realizowana jest w środowisku Xamarin w programie Visual Studio z wykorzystaniem języka C#. Dane niezbędne do działania aplikacji magazynowane są w plikach XML. Model systemu ekspertowego został przygotowany w oparciu o drzewa decyzyjne, natomiast projekt aplikacji opisuje diagram przypadków użycia oraz diagram klas. System ekspertowy, który został zaimplementowany w aplikacji, wykorzystuje do wygenerowania diety bazę wiedzy pozyskaną od ekspertów oraz moduł wnioskujący. Aplikacja może służyć zarówno celom użytkowym, jak i edukacyjnym. Będzie użyteczna dla osób ze specjalistycznym doświadczeniem, jak i bez niego.

EN

The aim of the study is to create application supporting the proper nutrition horses on the Android platform. The application is created in the environment Xamarin in Visual Studio IDE using CSharp language. The data needed for the application are stored in XML files. Expert system model was developed based on decision trees and the design of the application describes the use case diagram and class diagram. Expert system used in the application generates a diet using a knowledge base gained from experts and requesting module. The application can be used both practical purposes, as well as educational. It will be useful for people with specialized experience, and without it.

13

Prediction of displacement in the equine third metacarpal bone using a neural network prediction algorithm

Mouloodi Saeed, Rahmanpanah Hadi, Burvill Colin, Davies Helen M. S.

Biocybernetics and Biomedical Engineering

|

2020

|

Vol. 40, no. 2

849--863

EN

Bone is a nonlinear, inhomogeneous and anisotropic material. To predict the behavior of bones expert systems are employed to reduce the computational cost and to enhance the accuracy of simulations. In this study, an artificial neural network (ANN) was used for the prediction of displacement in long bones followed by ex-vivo experiments. Three hydrated third metacarpal bones (MC3) from 3 thoroughbred horses were used in the experiments. A set of strain gauges were distributed around the midshaft of the bones. These bones were then loaded in compression in an MTS machine. The recordings of strains, load, load exposure time, and displacement were used as ANN input parameters. The ANN which was trained using 3,250 experimental data points from two bones predicted the displace-ment of the third bone (R2 ≥ 0.98). It was suggested that the ANN should be trained using noisy data points. The proposed modification in the training algorithm makes the ANN very robust against noisy inputs measurements. The performance of the ANN was evaluated in response to changes in the number of input data points and then by assuming a lack of strain data. A finite element analysis (FEA) was conducted to replicate one cycle of force-displace-ment experimental data (to gain the same accuracy produced by the ANN). The comparison of FEA and ANN displacement predictions indicates that the ANN produced a satisfactory outcome within a couple of seconds, while FEA required more than 160 times as long to solve the same model (CPU time: 5 h and 30 min).

14

System ekspercki wspomagający dobór urządzeń adaptacyjnych dla kierowców z niepełnosprawnościami

Stasiak-Cieślak Beata, Grabarek Iwona

Prace Naukowe Politechniki Warszawskiej. Transport

|

2019

|

z. 124

161--170

PL

Artykuł przedstawia strukturę programu informatycznego wspomagającego dobór specjalistycznego oprzyrządowania w pojazdach dla kierowców z ograniczonymi funkcjami motorycznymi. Opracowany system umożliwia automatyzację doboru adaptacji poprzez zastosowanie regułowego systemu eksperckiego. W jego budowie wykorzystano również dotychczasowe doświadczenia i wiedzę specjalistów pozyskaną w oparciu o przegląd literatury z zakresu doboru adaptacji dla osób ze specyficznymi potrzebami motorycznymi.

EN

The article presents the structure of an IT program supporting the selection of specialized equipment in vehicles for drivers with limited motor functions. The developed system enables automation of adaptation selection through the use of a rule expert system. In its construction, the previous experience and knowledge of specialists obtained on the basis of literature review in the field of selection of adaptations for people with specific motor needs were also used.

15

Assesment of existing reinforced concrete structures with usage of the fuzzy logic - based expert system

Tur Viktar, Yalavaya Yuliya

Modern Engineering

|

2019

|

2

61--70

EN

Fuzzy logic is a useful tool when assessing the existing reinforced concrete structures. The introduction of expert system in assessing the technical condition of the existing structures built on the fuzzy logic represents a transition to a new and higher-quality level for the survey of constructions sites. As a result, it is seen that the assessment of the existing building with the usage of the proposed expert system complies with the estimation of the qualified experts.

16

An expert system for equipment selection of thin coal seam mining

Wang Chen, Chen Jie, Liu Yong, Jiang Chengyu

Gospodarka Surowcami Mineralnymi

|

2019

|

T. 35, z. 3

143--162

EN

As one of the key techniques in the fully mechanized mining process, equipment selection and matching has a great effect on security, production and efficiency. The selection and matching of fully mechanized mining equipment in thin coal seam are restricted by many factors. In fully mechanized mining (FMM) faced in thin coal seams (TCS), to counter the problems existing in equipment selection, such as many the parameters concerned and low automation, an expert system (ES) of equipment selection for fully mechanized mining longwall face was established. A database for the equipment selection and matching expert system in thin coal seam, fully mechanized mining face has been established. Meanwhile, a decision-making software matching the ES was developed. Based on several real world examples, the reliability and technical risks of the results from the ES was discussed. Compared with the field applications, the shearer selection from the ES is reliable. However, some small deviations existed in the hydraulic support and scraper conveyor selection. Then, the ES was further improved. As a result, equipment selection in fully mechanized mining longwall face called 4301 in the Liangshuijing coal mine was carried out by the improved ES. Equipment selection results of the interface in the improved ES is consistent with the design proposal of the 4301 FMM working face. The reliability of the improved ES can meet the requirements of the engineering. It promotes the intelligent and efficient mining of coal resources in China.

PL

Dobór sprzętu, jako jedna z kluczowych technik w pełni zmechanizowanego procesu wydobycia, ma ogromny wpływ na bezpieczeństwo, produkcję i wydajność. Wybór i dopasowanie w pełni zmechanizowanego sprzętu górniczego w cienkim pokładzie węgla jest ograniczone przez wiele czynników. W przypadku całkowicie zmechanizowanej ściany wydobywczej węgla (FMM) w cienkich pokładach (TCS) przeciwdziałanie problemom związanym z wyborem sprzętu, takim jak m.in.: wielość rozpatrywanych parametrów i niska automatyzacja, ustanowiono system ekspercki (ES) doboru sprzętu do w pełni zmechanizowanej ściany wydobywczej. Utworzono bazę danych systemu doboru i dopasowania systemu eksperckiego w cienkich pokładach węgla w pełni zmechanizowanej ściany wydobywczej. Jednocześnie opracowano oprogramowanie do podejmowania decyzji, dopasowane do ES. Na podstawie kilku rzeczywistych przykładów omówiono wiarygodność i ryzyko techniczne związane z wynikami ES. W porównaniu z zastosowaniem obecnym, wybór kombajnu systemem eksperckim (ES) jest niezawodny. Wystąpiły jednak pewne niewielkie odchylenia w wyborze stojaków hydraulicznych i przenośnika zgarniającego, następnie ES został ulepszony. W rezultacie poprawiono wybór sprzętu w całkowicie zmechanizowanej ścianie wydobywczej o nazwie 4301 w kopalni Liangshuijing. Interfejs wyników wyboru sprzętu w ulepszonym ES jest zgodny z propozycją projektu 4301 FMM roboczej ściany wydobywczej. Niezawodność ulepszonego ES może spełniać wymagania inżynieryjne. Promuje inteligentne i wydajne wydobycie zasobów węgla w Chinach.

17

Determining relevant biomarkers for prediction of breast cancer using anthropometric and clinical features: A comparative investigation in machine learning paradigm

Singh Bikesh Kumar

Biocybernetics and Biomedical Engineering

|

2019

|

Vol. 39, no. 2

393--409

EN

Early detection of breast cancer plays crucial role in planning and result of associated treatment. The purpose of this article is threefold: (i) to investigate whether or not clinical features obtained using routine blood analysis combined with anthropometric measurements can be utilized for envisaging breast cancer using predictive machine learning techniques; (ii) to explore the role of various machine learning components such as feature selection, data division protocols and classification to determine suitable biomarkers for breast cancer prediction; and (iii) to evaluate a recent database of clinical and anthropometric measurements acquired from normal individuals and individuals suffering from breast cancer. A database consisting of anthropometric and clinical attributes is used in the experiments. Various feature selection and statistical significance analysis methods are used to determine the relevance of various features. Furthermore, popular classifiers such as kernel based support vector machine (SVM), Naïve Bayesian, linear discriminant, quadratic discriminant, logistic regression, K-nearest neighbor (K-NN) and random forest were implemented and evaluated for breast cancer risk prediction using these features. Results of feature selection techniques indicate that among the nine features considered in this study, glucose, age and resistin are found to be most relevant and effective biomarkers for breast cancer prediction. Further, when these three features are used for classification, the medium K-NN classifier achieves the highest classification accuracy of 92.105% followed by medium Gaussian SVM which achieves classification accuracy of 83.684% under hold out data division protocol.

18

Intellectual wireless diagnosis of linearly distributed objects in real time

Krivoulya Gennady, Shcherbak Vladislav

Zeszyty Naukowe. Telekomunikacja i Elektronika / Uniwersytet Technologiczno-Przyrodniczy w Bydgoszczy

|

2018

|

nr 21

35--46

EN

Intellectual diagnostics of linearly distributed objects using wireless sensor networks is proposed. The solution of the task of functional diagnostics is realized by the expert system on the basis of the knowledge base in the form of a neuron-fuzzy network. For a technical object the current values of the diagnostic parameters are measured by wireless sensors. As an example, an expert diagnostic system for assessing the operability of a technical object.

PL

Zaproponowano diagnostykę intelektualną obiektуw rozproszonych liniowo z wykorzystaniem bezprzewodowych sieci czujników. Rozwiązanie zadania diagnostyki funkcjonalnej realizowane jest przez system ekspercki w oparciu o bazę wiedzy w postaci sieci neuronowo-rozmytej. W przypadku obiektu technicznego aktualne wartości parametrów diagnostycznych są mierzone przez czujniki bezprzewodowe. Jako przykład można podać ekspercki system diagnostyczny do oceny funkcjonalności obiektu technicznego.

19

Expert systems in assessing the construction process safety taking account of the risk of disturbances

Siemaszko A., Jakubczyk-Galczynska A., Grzyl B.

Scientific Journal of the Military University of Land Forces

|

2018

|

Vol. 50, No. 3(189)

218--227

EN

The objective of the paper is to present the issue of safety management during the construction process. Threats in the form of disturbances may occur in the preparatory phase, during the execution of the construction project and also during its operational use. The article presents the concept of applying the methodology based, among others, on Learning Bayesian Networks, Artificial Neural Networks and Support Vector Machine, which can be used for building a system for diagnostic and decision-making support at each stage of the construction process. The use of expert systems when it comes to making choices related to construction issues can bring many benefits to decision-makers, as it reduces the risk of taking a wrong decision, and, thus, increases the construction process safety.

20

The Response Surface Methodology revisited – comparison of analytical and non-parametric approaches

Osocha P.

Production Engineering Archives

|

2018

|

Vol. 20

49--53

EN

Since G.E.P. Box introduced central composite designs in early fifties of 20th century, the classic design of experiments (DoE) utilizes response surface models (RSM), however usually limited to the simple form of low-degree polynomials. In the case of small size datasets, the conformity with the normal distribution has very weak reliability and it leads to very uncertain assessment of a parameter statistical significance. The bootstrap approach appears to be better solution than – theoretically proved but only asymptotically equal – t distribution based evaluation. The authors presents the comparison of the RSM model evaluated by a classic method and bootstrap approach.